As an AI Engineer, you will be responsible for designing, developing, and implementing artificial intelligence solutions that enable intelligent automation, data analysis, and decision-making processes. You will work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to develop and deploy AI models and systems. Your role will involve researching, prototyping, and integrating cutting-edge AI technologies to solve complex business problems.
Responsibilities:
- Collaborate with data scientists and business stakeholders to understand project requirements and define AI solutions.
- Design and develop machine learning models, algorithms, and neural networks for data analysis, prediction, and decision-making.
- Collect, preprocess, and analyze large datasets to train and validate AI models.
- Implement AI solutions using programming languages (such as Python) and machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn).
- Optimize and fine-tune AI models for performance, scalability, and accuracy.
- Deploy AI models into production environments, ensuring stability, reliability, and security.
- Monitor and evaluate the performance of deployed models, and iterate on improvements.
- Collaborate with software engineers to integrate AI capabilities into existing or new software systems.
- Stay updated with the latest advancements in AI and machine learning research, and apply relevant techniques to solve business challenges.
- Document and communicate AI solutions, methodologies, and best practices to technical and non-technical stakeholders.
Requirements:
- Bachelor's or master's degree in Computer Science, Engineering, or a related field.
- Strong understanding of artificial intelligence, machine learning, and deep learning concepts.
- Hands-on experience with machine learning frameworks and libraries (such as TensorFlow, PyTorch, or scikit-learn).
- Proficiency in programming languages such as Python, Java, or C++.
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with big data processing frameworks (such as Hadoop or Spark) and SQL.
- Knowledge of cloud platforms (such as AWS, Azure, or Google Cloud) and experience with deploying AI models on cloud infrastructure.
- Strong problem-solving and analytical skills, with the ability to understand complex business requirements and translate them into AI solutions.
- Excellent communication and collaboration skills to work effectively in cross-functional teams.
- Ability to adapt to a fast-paced, dynamic work environment and quickly learn new technologies and techniques.